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Proceedings Paper

A spatial Poisson Point Process to classify coconut fields on Ikonos pansharpened images
Author(s): R. Teina; D. Béréziat; B. Stoll
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Paper Abstract

The goal of this study is to classify the coconut fields, observed on remote sensing images, according to their spatial distribution. For that purpose, we use a technique of point pattern analysis to characterize spatially a set of points. These points are obtained after a coconut trees segmentation process on Ikonos images. Coconuts' fields not following a Poisson Point Process are identified as maintained, otherwise other fields are characterized as wild. A spatial analysis is then used to establish locally the Poisson intensity and therefore to characterize the degree of wildness.

Paper Details

Date Published: 11 December 2008
PDF: 10 pages
Proc. SPIE 7149, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications II, 71491E (11 December 2008); doi: 10.1117/12.806422
Show Author Affiliations
R. Teina, Univ. Pierre et Marie Curie (France)
D. Béréziat, Univ. Pierre et Marie Curie (France)
B. Stoll, Univ. de la Polynésie Française (French Polynesia)


Published in SPIE Proceedings Vol. 7149:
Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications II
Allen M. Larar; Mervyn J. Lynch; Makoto Suzuki, Editor(s)

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